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      HPG pore: an efficient and scalable framework for nanopore sequencing data

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      , , , ,
      BMC Bioinformatics
      BioMed Central

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          Abstract

          Background

          The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable.

          Results

          Here we present HPG Pore, a toolkit for exploring and analysing nanopore sequencing data. HPG Pore can run on both individual computers and in the Hadoop distributed computing framework, which allows easy scale-up to manage the large amounts of data expected to result from extensive use of nanopore technologies in the future.

          Conclusions

          HPG Pore allows for virtually unlimited sequencing data scalability, thus guaranteeing its continued management in near future scenarios. HPG Pore is available in GitHub at http://github.com/opencb/hpg-pore.

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          Most cited references11

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            Improved data analysis for the MinION nanopore sequencer

            The Oxford Nanopore MinION sequences individual DNA molecules using an array of pores that read nucleotide identities based on ionic current steps. We evaluated and optimized MinION performance using M13 genomic dsDNA. Using expectation-maximization (EM) we obtained robust maximum likelihood (ML) estimates for read insertion, deletion and substitution error rates (4.9%, 7.8%, and 5.1% respectively). We found that 99% of high-quality ‘2D’ MinION reads mapped to reference at a mean identity of 85%. We present a MinION-tailored tool for single nucleotide variant (SNV) detection that uses ML parameter estimates and marginalization over many possible read alignments to achieve precision and recall of up to 99%. By pairing our high-confidence alignment strategy with long MinION reads, we resolved the copy number for a cancer/testis gene family (CT47) within an unresolved region of human chromosome Xq24.
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              MinION nanopore sequencing identifies the position and structure of a bacterial antibiotic resistance island.

              Short-read, high-throughput sequencing technology cannot identify the chromosomal position of repetitive insertion sequences that typically flank horizontally acquired genes such as bacterial virulence genes and antibiotic resistance genes. The MinION nanopore sequencer can produce long sequencing reads on a device similar in size to a USB memory stick. Here we apply a MinION sequencer to resolve the structure and chromosomal insertion site of a composite antibiotic resistance island in Salmonella Typhi Haplotype 58. Nanopore sequencing data from a single 18-h run was used to create a scaffold for an assembly generated from short-read Illumina data. Our results demonstrate the potential of the MinION device in clinical laboratories to fully characterize the epidemic spread of bacterial pathogens.
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                Author and article information

                Contributors
                jtarraga@cipf.es
                agallego@cipf.es
                Vicente.Arnau@uv.es
                im411@cam.ac.uk
                jdopazo@cipf.es
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                27 February 2016
                27 February 2016
                2016
                : 17
                : 107
                Affiliations
                [ ]Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012 Spain
                [ ]Departamento de Informática, ETSE, Universidad de Valencia, Valencia, Spain
                [ ]HPC Service, University Information Services, University of Cambridge, Cambridge, UK
                [ ]Bioinformatics of Rare Diseases (BIER), CIBER de Enfermedades Raras (CIBERER), Valencia, Spain
                [ ]Functional Genomics Node, (INB) at CIPF, Valencia, 46012 Spain
                Author information
                http://orcid.org/0000-0003-3318-120X
                Article
                966
                10.1186/s12859-016-0966-0
                4769497
                26921234
                2b490a8b-1cee-428c-84c8-165dc2c2a82c
                © Tarraga et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 September 2015
                : 22 February 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad (ES);
                Award ID: BIO2014-57291-R
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000780, European Commission (BE);
                Award ID: MLPM2012 318861
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003359, Generalitat Valenciana (ES);
                Award ID: PROMETEOII/2014/025
                Award Recipient :
                Categories
                Software
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                © The Author(s) 2016

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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